wallet-tracker

get_analytics

Read-only

Four aggregate views over the tracked wallets.



volume_trend shows activity over time. most_traded lists the tokens getting the

most attention. win_rate gives the distribution of outcomes. top_performers

ranks wallets by profit. Use for the overall picture rather than one wallet or

token.



blockchain: solana, bnb, base, eth or rh

mode: volume_trend, most_traded, win_rate or top_performers

wallet_type: kol, smart or whale (default kol)

period: 6h, 1d, 7d or 30d (default 7d)

limit: how many entries (default 20)

Input Schema

TableJSON Schema

Name	Required	Description	Default
`mode`	Yes	volume_trend shows activity over time. most_traded lists the tokens getting the most attention. win_rate gives the distribution of outcomes. top_performers ranks wallets by profit.
`limit`	No	How many entries to return. Keep it small: large results are trimmed to fit the context window anyway.
`period`	No	Statistics window: 6h, 1d, 7d or 30d. Longer windows return far more data and get trimmed harder, so prefer the shortest window that answers the question.	7d
`blockchain`	Yes	Blockchain. One of: solana, bnb, base, eth, rh. solana has kol, smart and whale wallets; bnb, base and rh have kol and smart; eth has kol only. rh is Robinhood Chain, an Ethereum L2.
`wallet_type`	No	Wallet type. kol is a Key Opinion Leader, an influencer whose calls move markets. smart is a wallet selected for its track record. whale is a large holder, Solana only.	kol

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds valuable behavioral context: trimming of large results, preference for shorter periods to avoid data loss, and blockchain-specific wallet type availability. These details go beyond the annotations and help the agent understand how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise: a two-sentence overview, a four-line mode list, and a five-line parameter list. Every sentence adds value; there is no redundancy or filler. The structure is front-loaded with purpose and then supported by parameter details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (5 parameters, 4 modes) and the presence of an output schema, the description covers the essential aspects: each mode's conceptual output, parameter defaults and constraints, and trimming behavior. It could mention pagination or rate limits, but overall it is sufficiently complete for an agent to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds a summary of parameters and some usage tips (e.g., 'prefer the shortest window'), but the schema already explains each parameter well. The description adds minor value but does not significantly enhance understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool provides 'four aggregate views over the tracked wallets' and lists each mode with a concise purpose (e.g., 'volume_trend shows activity over time'). It also differentiates from sibling tools by noting 'Use for the overall picture rather than one wallet or token.' This makes the tool's purpose and scope immediately clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear guidance on when to use the tool ('overall picture rather than one wallet or token'), implying alternatives like per-wallet or per-token tools. It does not explicitly list when-not-to-use or specific alternatives, but the context is strong enough for an agent to discern appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.2/5.0

Disambiguation5/5

Each tool targets a distinct function—comparing tokens vs. wallets, detecting bundles, retrieving historical vs. current signals, etc. Overlap is minimal, and descriptions clearly differentiate similar-sounding tools.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (compare_, detect_, get_, list_, lookup_), all in snake_case, making it easy to predict and understand the purpose of each tool.

Tool Count4/5

With 21 tools, the set is slightly above the typical 'well-scoped' range, but the breadth of functionality—covering wallet stats, tokens, signals, bundles, and comparisons across multiple blockchains—warrants the number. No tool feels redundant.

Completeness5/5

The tool surface covers essentially all aspects of wallet tracking: browsing, per-wallet stats/history/holdings/connections, token-level analysis, signals, bundles, leaderboards, and activity metrics. No obvious gaps for the stated purpose.

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